Segmentasi Citra Telur Ayam Berdasarkan Ukuran Menggunakan Algoritma Watershed

RAHAQLAKA, W. Bota (2025) Segmentasi Citra Telur Ayam Berdasarkan Ukuran Menggunakan Algoritma Watershed. Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.

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Abstract

Image segmentation is a technique in digital image processing that aims to separate background objects or other objects in an image based on certain characteristics. In this research process, there are obstacles, namely the manual egg classification process, such as inaccuracies in measurements and requiring a long processing time. Therefore, classifying eggs by size is crucial for maintaining quality standards and selling prices. This issue necessitates an automated egg grading system to save time. Therefore, this study aims to segment chicken egg images based on size using the Watershed algorithm, classifying chicken eggs into two groups: large and small. This method is used because it can separate adjacent objects and blur their boundaries based on their size, especially objects with similar shapes and those that touch each other. Watershed was chosen because of its advantage in precisely detecting boundaries between objects using a morphological approach. This method is also highly effective in distinguishing objects of different sizes based on topographic structure. The segmentation process begins with preprocessing, such as converting the image to grayscale, filtering, and thresholding. The Watershed algorithm is applied with marker-based segmentation techniques to ensure accurate separation of egg objects. The results of this study demonstrate the ability to differentiate chicken eggs based on size and can assist in automated egg classification and sorting systems in the livestock and food industries, thereby increasing production efficiency.

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